App Store Ratings Scraper vs Runner AI
Side-by-side comparison of features, pros & cons, pricing, and community votes (2026).
🏆 Runner AI leads with 380 upvotes
Export Google Play and App Store ratings
App Store Ratings Scraper is a powerful tool designed for developers, marketers, and competitive analysts who need to monitor app performance metrics across Google Play and the Apple App Store. By allowing users to easily input app URLs or IDs, it fetches comprehensive data such as ratings, review counts, prices, categories, developers, and other metadata. The exported datasets are clean and structured, making it straightforward to incorporate these insights into dashboards, BI reports, or ongoing monitoring systems. Its seamless integration with Apify datasets enhances data management and analysis, making it a valuable resource for competitive research, app optimization, and market intelligence. What sets this tool apart is its simplicity and focus on essential app metrics, combined with the ability to handle large data exports efficiently. It caters to a wide range of users from app developers tracking their app's reputation to marketing teams analyzing competitors. Its straightforward approach makes it accessible for users with varying levels of technical expertise, while its data accuracy and export functionality support data-driven decision making in a fast-paced app ecosystem.
Pros
- Easy to use with simple URL or ID input for quick data retrieval
- Exports clean, structured datasets suitable for BI and analysis
- Supports both Google Play and Apple App Store, ensuring comprehensive coverage
- Facilitates competitor analysis and market research effectively
- Automates the collection of ratings, reviews, and metadata
Cons
- Limited details on pricing structure, may require inquiry for exact costs
- Potential limitations on data volume or frequency depending on plan
- No mention of real-time updates or API access for automation
Best for
- • Monitoring app ratings and reviews over time for reputation management
- • Analyzing competitor app performance and user feedback
- • Gathering metadata and app details for market research
- • Tracking review counts and ratings trends for product improvements
Pricing: Likely operates on a freemium model with free data exports and paid plans for higher volume or additional features; specific pricing details are not explicitly provided and may require direct inquiry.
Build, optimize, and scale your AI-native store
Runner AI is an innovative SaaS platform designed for e-commerce entrepreneurs and website owners looking to maximize revenue through AI-driven optimization. Unlike traditional website builders, Runner AI not only creates your online store but also actively tests and refines various elements in the background. Its core strength lies in continuously running experiments to improve visitor engagement and conversion rates, effectively turning casual visitors into paying customers without manual intervention. With a focus on automation and data-driven decision making, Runner AI empowers users to scale their online stores efficiently while maintaining a high level of performance. Its seamless integration of website building and optimization makes it a compelling choice for those seeking an all-in-one AI-native solution to grow their e-commerce presence.
Pros
- Automates continuous website experiments to optimize conversions
- Combines website building and AI-driven optimization in one platform
- User-friendly interface suitable for non-technical users
- Focus on scaling revenue rather than just traffic generation
- Active community and positive early user feedback
Cons
- Relatively new with limited long-term case studies
- May have a learning curve for complete beginners
- Pricing details are not explicitly disclosed, which could impact budgeting
Best for
- • Launching a new e-commerce store and optimizing for early conversions
- • A/B testing website layouts, copy, and CTA placements automatically
- • Scaling existing online stores by continuously improving user experience
- • Running experiments to identify the most profitable product pages
Pricing: Likely adopts a subscription-based model with tiered plans, potentially including a free trial or freemium features. Specific pricing details are not publicly disclosed, but it is expected to scale with store size and feature requirements.